Data Scientist Training – Le Wagon – Company

Data scientists are responsible for processing large amounts of data and identifying patterns that support strategic decisions. A key part of a data scientist's work is developing predictive models using machine learning. This includes training, testing and validating algorithms applied to large data sets. These models are used to predict future developments. Techniques such as linear regression, decision trees, neural networks and deep learning are used. Data scientists select the appropriate algorithms and models based on the needs of the project and optimize them for maximum accuracy and efficiency.

In addition to modeling, the implementation of the developed models into operational systems is also part of the tasks of a data scientist. This can include integration with software solutions that continuously process and analyze real-time data. Data scientists often work closely with data engineers to ensure that the infrastructure is stable and scalable. You will typically need to have knowledge of mathematics, statistics, and programming languages ​​such as Python and SQL.

Data analysts focus on collecting, cleaning, and visualizing data to extract actionable business information. Your primary role is to monitor KPIs (Key Performance Indicators), create dashboards, and identify trends through in-depth analysis of data. The role requires knowledge of SQL, Excel and modern analysis tools such as Power BI or Google Looker Studio. While data analytics often involves less complex models than data science, the ability to clearly represent and interpret data is crucial.

Data engineers, on the other hand, are responsible for building and maintaining data infrastructures and pipelines that ensure that data can be collected, stored and processed efficiently. Your work includes the design and implementation of data architectures, management of databases and integration of data sources. Data engineers must be proficient in programming languages ​​such as Python and SQL as well as common technologies such as Docker, Kubernetes or BigQuery. Your work forms the basis for the successful use of data by data scientists and data analysts.

The Le Wagon coding bootcamp offers in-depth training programs that enable a successful career in the areas of data science, data analytics and data engineering. Le Wagon's programs are practice-oriented and help participants to acquire in-depth knowledge within a short period of time and test their skills in real projects. Le Wagon's Data Science Bootcamp includes intensive training in data science. The course covers advanced data analysis and statistics and provides knowledge in the development and implementation of machine learning models and the application of AI technologies. A particular highlight is the opportunity to build a strong portfolio by working on real projects. The course is designed to be flexible and can be completed in either a full-time format (completed in two months) or a part-time format (completed in seven months).

The Data Analytics Bootcamp at Le Wagon is aimed at anyone wanting to pursue a career in data analytics. The course includes data preparation and visualization and teaches how to monitor business KPIs and effectively use modern analysis tools such as Power BI and Google Looker Studio. Participants work on real data sets and create a portfolio that demonstrates their skills. Le Wagon's data engineering course, on the other hand, prepares students for the technical implementation and management of data infrastructures. The course enables you to create data pipelines and implement modern data architectures as well as apply technologies such as Docker, Kubernetes and BigQuery.

Le Wagon is a top-rated coding bootcamp with over 26,000 graduates worldwide. As a state-certified educational measure, it offers the option of fully financing further training with an educational voucher from the employment agency. Graduates benefit from individual support in their job search and a broad network of over 1,000 hiring partners. In addition, course participants receive lifelong access to learning materials to continuously develop their skills.